Jing Wang, Ting-Ting Dong and Ding-Hong Peng
Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial…
Abstract
Purpose
Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial for measuring the development progress and guiding continual improvements of HSM-GI. Since this process of HSM-GI can be regarded as complex and interactive, a holistic picture is often required to describe the interrelations of its antecedents and consequences. In this respect, this study aims to construct a causality network indicator system and proposes a synergy evaluation method for HSM-GI.
Design/methodology/approach
Firstly, based on the Driver force-State-Response (DSR) causal-effect framework, this study constructs a holistic indicator system to analyze the interactions between environmental and human concerns of HSM-GI. Secondly, owing to the imprecision of human cognition and synergy interaction in the evaluation process, a flexible hesitant fuzzy (HF) superiority-inferiority synergetic evaluation method is presented. This method quantifies the strengths of causal relationships and expresses the incentives and constraints attitudes of humans. Finally, the proposed framework is applied to six HSMs in the electronic technology industry.
Findings
The driving force and state of the HSM-GI system exhibit an upward trend, while the response continues to decline due to changing market demands. The order and synergy degree have shown an increasing trend during 2021–2023, particularly significant for BOE and Haier Smart Home. HSM-GI systems with higher scores mostly have functional coordination and a coherent synergy structure.
Originality/value
This study demonstrates the proposed approach’s applicability and assists policymakers in formulating targeted strategies for green innovation systems.
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Zidan Tian, Ting Wang, Kaiwen Jiang, Qinghua He, Yutong Xue and Xiaoyan Chen
Recent studies suggested that owner dynamic capabilities (ODCs) enabling public owners of megaprojects to activate, orchestrate and reorganize resources to uncertainties were…
Abstract
Purpose
Recent studies suggested that owner dynamic capabilities (ODCs) enabling public owners of megaprojects to activate, orchestrate and reorganize resources to uncertainties were beneficial to improving the project resilience of megaprojects. However, most of them pay insufficient attention to the specific context of long cycles and deep uncertainty in megaprojects, neglecting the causal complexity that different dimensions of ODCs and learning mechanisms interact with each other in terms of enhancing project resilience. Therefore, this study aims to systematically unveil the complex causality among ODCs, learning mechanisms and project resilience of megaprojects.
Design/methodology/approach
This study introduces a configurational perspective to explore how multi-dimensional ODCs combine to improve project resilience in megaprojects along with different organizational learning mechanisms and learning orientations. Based on 330 ODC events in 19 construction megaprojects, a multi-temporal crisp-set qualitative comparative analysis method is adopted to extract configurations of ODCs for project resilience improvement and unveil their evolution features over the whole megaproject lifecycle.
Findings
Six configurations are identified for improving project resilience in megaprojects, including cognition-dominant, cognition-deficient, transformation-dominant, innovation-driven, value-co-creation and exploitative-transformation configurations. The results also indicate that distinct megaproject stages appeal to corresponding ODC configurations for project resilience improvement under unique uncertain contexts.
Originality/value
This study not only makes theoretical contributions to the literature on dynamic capability and project resilience in the megaproject management field but also provides useful practical guidance for public owners of megaprojects to better utilize ODCs for project resilience improvement.
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Małgorzata Bartosik-Purgat and Wiktoria Rakowska
The main purpose of the study is to identify the differences and similarities in the communication between B2B participants in cross-cultural environments.
Abstract
Purpose
The main purpose of the study is to identify the differences and similarities in the communication between B2B participants in cross-cultural environments.
Design/methodology/approach
The research methods used in the study are two-fold: the literature analysis is complemented by primary qualitative research conducted in small- and medium-sized enterprises operating in Poland and doing business internationally. The research was focused on two culturally different markets: China and the United States. In the empirical research, the authors used one of the qualitative methods – Individual Depth Interview (IDI).
Findings
General findings showed that the strongest influence of culture was identified among older (+50 years old) business partners. The younger ones are eager to adapt and try to understand others' viewpoints. The research results may be used in creating business communication models in the countries researched for companies that plan to enter both American and Chinese markets.
Practical implications
The results of the study may have useful applied managerial value and be used in cooperation between SMEs' B2B business partners, not only from Poland but also from the whole region of Central and Eastern Europe and the United States and China.
Social implications
The findings may help to understand and communicate with culturally different social groups such as co-workers, students, teachers, etc.
Originality/value
The research presented in the paper covers the gap in the literature because it relates to some new factors (like cultural heritage, age and type of industry) which determine the effectiveness of personal business communication between partners in the international marketplace.
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Tang Ting, Md Aslam Mia, Md Imran Hossain and Khaw Khai Wah
Given the growing emphasis among scholars, practitioners and policymakers on financial sustainability, this study aims to explore the applicability of machine learning techniques…
Abstract
Purpose
Given the growing emphasis among scholars, practitioners and policymakers on financial sustainability, this study aims to explore the applicability of machine learning techniques in predicting the financial performance of microfinance institutions (MFIs).
Design/methodology/approach
This study gathered 9,059 firm-year observations spanning from 2003 to 2018 from the World Bank's Mix Market database. To predict the financial performance of MFIs, the authors applied a range of machine learning regression approaches to both training and testing data sets. These included linear regression, partial least squares, linear regression with stepwise selection, elastic net, random forest, quantile random forest, Bayesian ridge regression, K-Nearest Neighbors and support vector regression. All models were implemented using Python.
Findings
The findings revealed the random forest model as the most suitable choice, outperforming the other models considered. The effectiveness of the random forest model varied depending on specific scenarios, particularly the balance between training and testing data set proportions. More importantly, the results identified operational self-sufficiency as the most critical factor influencing the financial performance of MFIs.
Research limitations/implications
This study leveraged machine learning on a well-defined data set to identify the factors predicting the financial performance of MFIs. These insights offer valuable guidance for MFIs aiming to predict their long-term financial sustainability. Investors and donors can also use these findings to make informed decisions when selecting their potential recipients. Furthermore, practitioners and policymakers can use these findings to identify potential financial performance vulnerabilities.
Originality/value
This study stands out by using a global data set to investigate the best model for predicting the financial performance of MFIs, a relatively scarce subject in the existing microfinance literature. Moreover, it uses advanced machine learning techniques to gain a deeper understanding of the factors affecting the financial performance of MFIs.
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Muhammad Asghar Ali, Ding Hooi Ting, Muhammad Umer Azeem and Amir Zaib Abbasi
This paper aims to investigate the impact of perceived usefulness of online reviews and crowd cues on restaurant selection. In addition, the authors also examine the moderating…
Abstract
Purpose
This paper aims to investigate the impact of perceived usefulness of online reviews and crowd cues on restaurant selection. In addition, the authors also examine the moderating role of perceived crowding and gender in this process.
Design/methodology/approach
The proposed hypotheses were tested with survey data (N = 200) collected from customers visiting full-service restaurants in Malaysia. The data were analyzed using SEM through Smart PLS.
Findings
The findings supported that the perceived usefulness of online reviews and perceived crowding have a positive effect on a consumer's purchase intentions, i.e. their decision of restaurant selection. Besides, a higher level of perceived crowding strengthens the relationship between the perceived usefulness of online reviews and their purchase intentions. This finding delineates that consumers prefer to dine in a crowded place with useful online reviews in an unfamiliar place. Finally, the results show that the effect of the usefulness of online reviews on purchase intentions does not vary with respect to gender (no significant contingent effect). However, the effect of perceived crowding varies with respect to gender – male customers have higher intentions to join crowded restaurants as compared to females.
Research limitations/implications
Limitation of this study is its cross-sectional research design; data were collected in a single time frame. Longitudinal research design can be used to get in-depth knowledge of this phenomenon. Secondly, a non-probability sampling technique was used in this study, future research can used probability sampling technique to enhance generalizability of the study. Moreover, this study focused on the human crowding aspect, future studies can cover both aspects of crowding (human crowding and spatial crowding) in retailing or other service sectors (Blut and Iyer, 2020).
Practical implications
This study has multiple practical implications.
Originality/value
This study extends the current research on usefulness of online reviews and perceived crowding by investigating its direct and conditional effects. Specifically, the authors contribute in extant research by explaining its differential effects for male and female customers, when they select which restaurants to dine.
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Mosa Abdelgelil Amin, Eman Mohamed Abdelmaged, Awad Elsayed Ibrahim and Tarek Abdelfattah
This study aims to investigate the relationship between Chief Executive Officer (CEO) characteristics and audit report lag (ARL) in Egypt, an emerging economy characterized by…
Abstract
Purpose
This study aims to investigate the relationship between Chief Executive Officer (CEO) characteristics and audit report lag (ARL) in Egypt, an emerging economy characterized by high power distance and a culture of secrecy. The study utilizes a theoretical framework that integrates agency theory, stewardship theory, and upper echelons theory as the foundation for examining this relationship.
Design/methodology/approach
The sample consists of 587 firm-year observations from non-financial firms listed on the EGX100, covering the period from 2012 to 2019. The primary variable of the study (ARL) is measured using different proxies. The analysis utilizes both Ordinary Least Squares (OLS) and logistic regression models, with additional analysis considering CEO power and using board gender diversity as a moderating variable.
Findings
The study finds that CEO characteristics significantly affect ARL, demonstrating a negative association between CEO ownership, founder status, family ties, duality and ARL. These findings remain robust after a series of tests using alternative measures. Additional analysis reveals that CEO power is negatively and significantly related to ARL. Interestingly, the negative association between CEO characteristics and ARL is more pronounced in boards without female members.
Originality/value
Although extensive research has been conducted on the factors determining ARL, few studies have examined the impact of CEO characteristics on ARL, particularly in emerging economies such as Egypt. The business environment in Egypt is characterized by high power distance and a secretive culture, providing a unique context for this study.
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Ming-Chang Huang, Ming-Kun Tsai, Tzu-Ting Chen, Ya-Ping Chiu and Wan-Jhu You
This study aims to empirically investigate how knowledge paradox affects collaboration performance. Knowledge paradox, which arises from the simultaneous need for knowledge…
Abstract
Purpose
This study aims to empirically investigate how knowledge paradox affects collaboration performance. Knowledge paradox, which arises from the simultaneous need for knowledge sharing and protection, is common in interorganizational collaboration. Using the ambidexterity perspective, this paper aims to reexamine the effect of the knowledge paradox on collaborative performance to explore the moderating roles of structural and contextual ambidexterity.
Design/methodology/approach
This study used a sample of 153 firms involved in vertical and horizontal collaboration, collected via questionnaires. Hypotheses were tested using hierarchical regression analysis.
Findings
This study demonstrates that the stronger the knowledge paradox is, the higher the potential for value creation. Thus, knowledge paradox has a positive impact on collaborative performance. The functions of structural ambidexterity and contextual ambidexterity strengthen this positive relationship.
Originality/value
This paper not only expands the theoretical application of the knowledge paradox and ambidexterity theory in the context of interorganizational relationships but also provides significant managerial implications. By comprehending the dynamics of the knowledge paradox and the role of ambidexterity, managers can make well-informed decisions to enhance their collaborative performance.
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Liu Ting and Jiseon Ahn
Due to increasing interest in sustainability, consumers prioritize environmentally friendly consumption across various service sectors. This study aims to examine how…
Abstract
Purpose
Due to increasing interest in sustainability, consumers prioritize environmentally friendly consumption across various service sectors. This study aims to examine how environment-related attributes of food delivery services affect customer behavior. Specifically, the authors use the stimulus-organism-response framework to explore how environmentally friendly food packages correlate with customers’ environmental support and patronage behavior.
Design/methodology/approach
The authors collected data from US food delivery service customers. To test the hypotheses, the authors used partial least squares structural equation modeling.
Findings
The authors find that customers’ perceptions of the environmental friendliness of food packages influence their satisfaction and trust, which in turn affect their environmental support and patronage behaviors. Also, customers’ trust and satisfaction mediate the relationship between their food consumption experience and its outcomes. The authors further explore demographic factors that influence the proposed relationships.
Originality/value
Due to the popularity of food delivery services, this study has theoretical and practical implications for restaurant service providers and highlights the potential of environmentally friendly packaging to increase both environmental support and loyal behavior.
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Shuang Tian, Lin Wu and Kulwant S. Pawar
Characterised by simultaneous food waste and shortages, our current food system is far from sustainable. Industry 4.0 has responded with technology-enabled innovations, including…
Abstract
Purpose
Characterised by simultaneous food waste and shortages, our current food system is far from sustainable. Industry 4.0 has responded with technology-enabled innovations, including digital food-sharing platforms aimed at facilitating the efficient redistribution of surplus food. However, potential users often express reluctance to adopt such platforms, prompting this study to explore the underlying reasons for their hesitations.
Design/methodology/approach
This study was conducted in China, the world’s largest platform economy, where food-sharing platforms are notably absent. Using a vignette-based qualitative approach, semi-structured interviews were conducted with 35 potential users. The data were analysed through thematic analysis to uncover insights into adoption intentions.
Findings
The findings highlight the relevance of factors identified in existing technology acceptance theories, such as performance expectancy, effort expectancy, social influence, hedonic motivation, facilitating conditions and price value, in shaping adoption intentions. Additionally, content-specific and context-specific factors – such as trust in other users and the platform, concerns about “losing face” (mianzi) and safety concerns during the pandemic – emerged as critical influences on users' decisions to engage with these platforms.
Originality/value
This study contributes to scholarly discussions on enhancing the effectiveness of new technological innovations for food supply chain sustainability. The theoretical contributions expand the technology acceptance literature by incorporating factors related to platform service content and operating context.
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Hsien Chun Chen, Chin Tung Stewart Ng, I-Heng Chen, Yi-Ting Chen, Michal Polacek and Ying-Lun Liang
The study explores the mechanism between employee demand–ability fit and promotability ratings. Moreover, we examine whether political skill moderates the relationship above.
Abstract
Purpose
The study explores the mechanism between employee demand–ability fit and promotability ratings. Moreover, we examine whether political skill moderates the relationship above.
Design/methodology/approach
The present study received 260 effective supervisor-rated questionnaires from various industries in Taiwan.
Findings
The results reveal that employee demand–ability fit positively relates to promotability ratings, and task performance mediates the above relationship. In addition, political skill positively moderates the relationship between employee demand–ability fit and task performance.
Originality/value
We used the supervisor rating for our variables to test the hypotheses.